Glaucylara Reis Geovanini1, Geraldo Lorenzi-Filho2, Lilian K de Paula2, Camila Maciel Oliveira3, Rafael de Oliveira Alvim3, Felipe Beijamini4, André Brooking Negrão5, Malcolm von Schantz6, Kristen L Knutson7, José Eduardo Krieger3, Alexandre Costa Pereira3. 1. Genetics and Molecular Cardiology Laboratory, Heart Institute (InCor) - University of São Paulo, Medical School, São Paulo, Brazil; Sleep Laboratory, Pulmonary Division, Heart Institute (InCor) - University of São Paulo, Medical School, São Paulo, Brazil. Electronic address: gal.reis@globo.com. 2. Sleep Laboratory, Pulmonary Division, Heart Institute (InCor) - University of São Paulo, Medical School, São Paulo, Brazil. 3. Genetics and Molecular Cardiology Laboratory, Heart Institute (InCor) - University of São Paulo, Medical School, São Paulo, Brazil. 4. Federal University of Fronteira do Sul, Realeza, PR, Brazil. 5. Genetics and Molecular Cardiology Laboratory, Heart Institute (InCor) - University of São Paulo, Medical School, São Paulo, Brazil; Department of Psychiatry, University of São Paulo, School of Medicine, São Paulo, Brazil. 6. Department of Psychiatry, University of São Paulo, School of Medicine, São Paulo, Brazil; Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK. 7. Center for Circadian and Sleep Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Abstract
AIM: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration. METHODS: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration). RESULTS: The sample mean age was 43 ± 16 years, 66% were female, and mean body mass index (BMI) was 26 ± 5 kg/m2. Only 20% were classified as obese (BMI ≥30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score ≥5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apnea-hypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004). CONCLUSION: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status.
AIM: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration. METHODS: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration). RESULTS: The sample mean age was 43 ± 16 years, 66% were female, and mean body mass index (BMI) was 26 ± 5 kg/m2. Only 20% were classified as obese (BMI ≥30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score ≥5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apnea-hypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004). CONCLUSION: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status.
Authors: Julia Nowowiejska; Anna Baran; Marta Lewoc; Paulina Grabowska; Tomasz W Kaminski; Iwona Flisiak Journal: J Clin Med Date: 2021-02-09 Impact factor: 4.241